Extracting Information from Flexible Receptor-Flexible Ligand Docking Experiments
BSB '08 Proceedings of the 3rd Brazilian symposium on Bioinformatics: Advances in Bioinformatics and Computational Biology
Automating molecular docking with explicit receptor flexibility using scientific workflows
BSB'07 Proceedings of the 2nd Brazilian conference on Advances in bioinformatics and computational biology
Discretization of flexible-eceptor docking data
BSB'10 Proceedings of the Advances in bioinformatics and computational biology, and 5th Brazilian conference on Bioinformatics
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Among different alternatives to consider the receptor flexibility in molecular docking experiments we opt to execute a series of docking using receptor snapshots generated by molecular dynamics simulations. Our target is the InhA enzyme from Mycobacterium tuberculosis bound to NADH, TCL, PIF and ETH ligands. After testing some mining strategies on these data, we conclude that, to obtain better outcomes, the development of an organized repository is especially useful. Thus, we built a comprehensive and robust database called FReDD to store the InhA-ligand docking results. Using this database we concentrate efforts on data mining to explore the docking results in order to accelerate the identification of promising ligands against the InhA target.